Integrating IoT and Cloud Analytics for Real-Time Monitoring of Post-Surgical Recovery in Maxillofacial Patients

Abstract

Post-surgical recovery in maxillofacial patients is a complex process requiring precise monitoring of physiological, behavioral, and environmental parameters to prevent complications and ensure optimal healing. This study presents a real-time health monitoring framework using an integrated Internet of Things (IoT) and cloud-based analytics system tailored for post-operative maxillofacial care. Wearable biosensors—including temperature, heart rate, EMG, and jaw motion sensors—were deployed on 30 patients undergoing mandibular and maxillary surgeries at three clinical sites in India. These sensors transmitted continuous health metrics to a secured cloud platform via Wi-Fi and LTE. Advanced analytics, including anomaly detection algorithms and recovery pattern forecasting models, were implemented using AWS IoT Core and Azure Machine Learning. Recovery indicators such as edema, pain flare-ups, and muscle reactivity were visualized using a real-time dashboard, allowing remote intervention by healthcare professionals. The results indicated that patients monitored with the IoT-cloud system had a 32% reduction in unplanned readmissions and showed significantly faster wound stabilization compared to traditionally monitored groups. Moreover, temporal analytics revealed peak healing between postoperative days 4 to 7, enabling dynamic adjustment of pain management protocols. This multidisciplinary solution shows the potential of transformative potential of IoT and cloud-based technologies in enriching patient-centric recovery pathways, minimizing the clinical burden, and facilitating predictive healthcare in oral and maxillofacial surgery.